Legionnaires’ Disease Outbreaks
Holly Kessler
August 10, 2016
The coordinates of the Legionnairess Disease outbreaks will be used to gather weather data from surrounding stations. The averages of the data will be taken and outputted into a graph containing data from the last 10 years before the outbreak.
First I installed and downloaded the packages needed including rnoaa from github.
library(devtools)
install_github("geanders/rnoaa")library(devtools)
library(rnoaa)
library(riem)
library(countyweather)
library(dplyr)
library(plyr)
library(tidyr)
library(weathermetrics)
library(ggplot2)
library(lubridate)I created a data frame including the locations of each outbreak. I found the coordinates at http://maps.cga.harvard.edu/gpf/ and crossed checked them with Google coordinates. The other data in this set are year of outbreak and the year 10 years before the outbreak, onset date, and 14 days before the onset date.
| id | file_id | latitude | longitude | year_min | date_min | year_max | date_max | onset | before_onset |
|---|---|---|---|---|---|---|---|---|---|
| portugal | portugal | 38.96 | -8.99 | 2004 | 2004-01-01 | 2014 | 2014-12-31 | 2004-10-14 | 2004-09-30 |
| pittsburgh | pittsburgh | 40.43 | -79.98 | 2002 | 2002-01-01 | 2012 | 2012-12-31 | 2012-08-26 | 2012-08-12 |
| quebec | quebec | 46.85 | -71.34 | 2002 | 2002-01-01 | 2012 | 2012-12-31 | 2012-07-18 | 2012-07-04 |
| stoke-on-trent | stoke_on_trent | 53.02 | -2.15 | 2002 | 2002-01-01 | 2012 | 2012-12-31 | 2012-07-02 | 2012-06-18 |
| edinburgh | edinburgh | 55.94 | -3.20 | 2002 | 2002-01-01 | 2012 | 2012-12-31 | 2012-05-01 | 2012-04-17 |
| miyazaki | miyazaki | 31.89 | 131.34 | 1992 | 1992-01-01 | 2002 | 2002-12-31 | 2002-07-18 | 2002-07-04 |
| pas-de-calais | pas_de_calais | 50.51 | 2.37 | 1993 | 1993-01-01 | 2003 | 2003-12-31 | 2003-11-28 | 2003-11-14 |
| pamplona | pamplona | 42.81 | -1.65 | 1996 | 1996-01-01 | 2006 | 2006-12-31 | 2006-06-01 | 2006-05-18 |
| rapid city | rapid_city | 44.06 | -103.22 | 1995 | 1995-01-01 | 2005 | 2005-12-31 | 2005-05-26 | 2005-05-12 |
| sarpsborg | sarpsborg | 59.28 | 11.08 | 1995 | 1995-01-01 | 2005 | 2005-12-31 | 2005-05-12 | 2005-04-28 |
| barrow-in-furness | barrow_in_furness | 54.10 | -3.22 | 1992 | 1992-01-01 | 2002 | 2002-12-31 | 2002-07-30 | 2002-07-16 |
| murcia | murcia | 37.98 | -1.12 | 1991 | 1991-01-01 | 2001 | 2001-12-31 | 2001-06-26 | 2001-06-12 |
| melbourne | melbourne | -37.86 | 145.07 | 1990 | 1990-01-01 | 2000 | 2000-12-31 | 2000-04-17 | 2000-04-03 |
| bovenkarspel | bovenkarspel | 52.70 | 5.24 | 1989 | 1989-01-01 | 1999 | 1999-12-31 | 1999-02-25 | 1999-02-11 |
| london | london | 51.52 | -0.10 | 1979 | 1979-01-01 | 1989 | 1989-12-31 | 1989-01-01 | 1988-12-18 |
| sydney | sydney | -33.85 | 150.93 | 2006 | 2006-01-01 | 2016 | 2016-12-31 | 2016-04-25 | 2016-04-11 |
| genesee1 | genesee1 | 43.09 | -83.63 | 2004 | 2004-01-01 | 2014 | 2014-12-31 | 2014-06-06 | 2014-05-23 |
| genesee2 | genesee2 | 43.09 | -83.63 | 2005 | 2005-01-01 | 2015 | 2015-12-31 | 2015-05-04 | 2015-04-20 |
| columbus | columbus | 39.98 | -82.99 | 2003 | 2003-01-01 | 2013 | 2013-12-31 | 2013-07-09 | 2013-06-25 |
| bronx | bronx | 40.82 | -73.92 | 2005 | 2005-01-01 | 2015 | 2015-12-31 | 2015-07-12 | 2015-06-28 |
The next function will download information from all of the stations. It only needs to be downloaded once per session. It will take a couple minutes to download.
I created a loop to get a list of the stations within 30 km of the location.
station_data <- ghcnd_stations()[[1]]
df <- list()
for(i in 1:length(outbreak_loc$id))
{
df[[i]] <- (meteo_nearby_stations(lat_lon_df = outbreak_loc[i,],
station_data = station_data,
var = c("PRCP","TAVG","TMAX","TMIN",
"AWND","MDPR"),
year_min = outbreak_loc[i, "year_min"],
year_max = outbreak_loc[i, "year_max"],
radius = 30)[[1]])
}
names(df) <- outbreak_loc$id
stations <- df
saveRDS(stations, file = "stations.RData")stations <- readRDS("stations.RData")
stations## $portugal
## [1] id name latitude longitude distance
## <0 rows> (or 0-length row.names)
##
## $pittsburgh
## id name latitude longitude distance
## 1 US1PAAL0014 PA PITTSBURGH 1.6 SW 40.4226 -79.9974 1.687108
## 2 US1PAAL0017 PA WHITEHALL 1.0 SW 40.3475 -80.0022 9.364279
## 3 USW00014762 PA PITTSBURGH ALLEGHENY CO AP 40.3547 -79.9217 9.720301
## 4 US1PAAL0011 PA WEST MIFFLIN 1.3 SW 40.3466 -79.9283 10.255413
## 5 US1PAAL0031 PA SCOTT TOWNSHIP 1.3 NW 40.3978 -80.0967 10.508788
## 6 USC00360861 PA BRADDOCK LOCK 2 40.3917 -79.8594 11.063215
## 7 US1PAAL0009 PA PATHFINDER 40.3416 -80.0485 11.414110
## 8 USC00362574 PA EMSWORTH L/D OHIO RVR 40.5019 -80.0833 11.844197
## 9 US1PAAL0016 PA GLENSHAW 1.3 NW 40.5488 -79.9800 13.209957
## 10 USC00365573 PA MCKEESPORT 40.3392 -79.8603 14.308275
## 11 US1PAAL0008 PA UPPER ST. CLAIR 1.7 WNW 40.3412 -80.1026 14.329100
## 12 US1PAAL0020 PA ALLISON PARK 0.7 W 40.5610 -79.9708 14.587294
## 13 US1PAAL0023 PA SOUTH PARK TOWNSHIP 0.2 NW 40.2989 -79.9970 14.648635
## 14 US1PAAL0003 PA SOUTH FAYETTE 2 SE 40.3381 -80.1159 15.392161
## 15 US1PAAL0001 PA BRIDGEVILLE 1.4 SW 40.3417 -80.1229 15.584945
## 16 US1PAAL0004 PA PENN HILLS 1.5 E 40.4759 -79.7982 16.207171
## 17 USC00360022 PA ACMETONIA LOCK 3 40.5361 -79.8153 18.254228
## 18 US1PAAL0006 PA MCDONALD 2.5 ENE 40.3822 -80.1871 18.323293
## 19 US1PAWS0005 PA MCMURRAY 0.2 NE 40.2831 -80.0857 18.628831
## 20 USW00094823 PA PITTSBURGH INTL AP 40.4847 -80.2144 20.743637
## 21 US1PAAL0030 PA CARNOT-MOON 0.9 S 40.5061 -80.2119 21.364459
## 22 USC00366111 PA MURRYSVILLE 2 SW 40.4119 -79.7244 21.730660
## 23 US1PAWT0001 PA NORTH IRWIN 2.5 WSW 40.3243 -79.7556 22.348628
## 24 USC00365918 PA MOON TOWNSHIP 40.5319 -80.2172 23.040372
## 25 USC00363343 PA GLENWILLARD DASHIELDS 40.5514 -80.2167 24.143027
## 26 US1PAWT0010 PA MURRYSVILLE 1.5 WSW 40.4317 -79.6813 25.282776
## 27 US1PAAL0012 PA SOUTH HEIGHTS 1.5 S 40.5533 -80.2379 25.760534
##
## $quebec
## id name latitude longitude distance
## 1 CA007011309 QC CHARLESBOURG PARC ORLEAN 46.8667 -71.2667 5.874619
## 2 CA007016294 QC QUEBEC/JEAN LESAGE INTL A 46.8000 -71.3833 6.462488
## 3 CA00701S001 QC QUEBEC/JEAN LESAGE INTL 46.8000 -71.3833 6.462488
## 4 CA00701Q004 QC STE-FOY (U. LAVAL) 46.7833 -71.2833 8.580380
## 5 CA007010565 QC BEAUPORT 46.8333 -71.2000 10.808994
## 6 CA007018572 QC VALCARTIER 46.9000 -71.5000 13.372471
## 7 CA007024254 QC LAUZON 46.8167 -71.1000 18.628731
## 8 CA007020567 QC BEAUSEJOUR 46.6667 -71.1667 24.283856
## 9 CA007041330 QC CHATEAU RICHER 46.9667 -71.0333 26.668362
##
## $`stoke-on-trent`
## [1] id name latitude longitude distance
## <0 rows> (or 0-length row.names)
##
## $edinburgh
## [1] id name latitude longitude distance
## <0 rows> (or 0-length row.names)
##
## $miyazaki
## id name latitude longitude distance
## 1 JA000047830 MIYAZAKI 31.933 131.417 8.699733
## 2 JA000047829 MIYAKONOJO 31.733 131.083 29.908209
##
## $`pas-de-calais`
## [1] id name latitude longitude distance
## <0 rows> (or 0-length row.names)
##
## $pamplona
## id name latitude longitude distance
## 1 SPE00120350 PAMPLONA (OBSERVATORIO) 42.8175 -1.6364 1.387848
## 2 SPE00120359 PAMPLONA 42.7767 -1.6500 3.702791
##
## $`rapid city`
## id name latitude longitude distance
## 1 USC00396948 SD RAPID CITY WFO 44.0728 -103.2108 1.601898
## 2 USC00396947 SD RAPID CITY 4NW 44.1150 -103.2828 7.909484
## 3 USW00024090 SD RAPID CITY RGNL AP 44.0433 -103.0536 13.427258
## 4 USC00394343 SD JOHNSON SIDING 44.0839 -103.4342 17.317536
## 5 USR0000SBAK SD BAKER PARK SOUTH DAKOTA 43.9792 -103.4250 18.692682
## 6 USC00396427 SD PACTOLA DAM 44.0622 -103.4819 20.928415
## 7 USC00394556 SD KEYSTONE 43.9039 -103.4100 23.073539
## 8 USR0000SNEM SD NEMO SOUTH DAKOTA 44.1917 -103.5097 27.370234
## 9 USC00395870 SD MT RUSHMORE NATL MEM 43.8769 -103.4578 27.869317
## 10 USR0000SMRU SD MT. RUSHMORE SOUTH DAKOTA 43.8750 -103.4583 28.051427
## 11 USC00393775 SD HERMOSA 3 SSW 43.8069 -103.2131 28.148859
##
## $sarpsborg
## id name latitude longitude distance
## 1 NOE00109849 SARPSBORG 59.2856 11.1144 2.050694
## 2 NOE00134298 FLOTER 59.4964 11.0131 24.358920
## 3 NOE00100575 HALDEN 59.1225 11.3883 24.795447
## 4 NOE00109786 HVALER 59.0358 11.0517 27.201683
## 5 NOE00109876 MOSS BRANNSTASJON 59.4428 10.6842 28.822789
## 6 NOE00109867 MOSS 59.4339 10.6667 29.008867
##
## $`barrow-in-furness`
## [1] id name latitude longitude distance
## <0 rows> (or 0-length row.names)
##
## $murcia
## id name latitude longitude distance
## 1 SPE00120323 MURCIA 38.0028 -1.1692 5.001690
## 2 SPE00120332 MURCIA/ALCANTARILLA 37.9578 -1.2294 9.902609
##
## $melbourne
## id name latitude longitude distance
## 1 ASN00086018 CAULFIELD (RACECOURSE) -37.8795 145.0368 3.632396
## 2 ASN00086304 HAWTHORN (SCOTCH COLLEGE) -37.8361 145.0294 4.446429
## 3 ASN00086095 PRAHRAN (COMO HOUSE) -37.8376 145.0048 6.243145
## 4 ASN00086088 OAKLEIGH (METROPOLITAN GOLF CL -37.9142 145.0935 6.369850
## 5 ASN00086012 BOX HILL AGED MENS RETREAT -37.8364 145.1364 6.393542
## 6 ASN00086006 BENTLEIGH -37.9279 145.0749 7.562369
## 7 ASN00086033 BRIGHTON (DENDY PARK BOWLING C -37.9252 145.0254 8.238821
## 8 ASN00086232 MELBOURNE BOTANICAL GARDENS -37.8303 144.9767 8.833034
## 9 ASN00086279 NORTHCOTE -37.7797 145.0314 9.551015
## 10 ASN00086316 VERMONT TRANSPORT RESEARCH -37.8587 145.1847 10.070617
## 11 ASN00086071 MELBOURNE REGIONAL OFFICE -37.8075 144.9700 10.545355
## 12 ASN00086020 CHELTENHAM KINGSTON CENTRE -37.9551 145.0782 10.599081
## 13 ASN00086303 GLEN WAVERLEY (GOLF COURSE) -37.8886 145.1928 11.237859
## 14 ASN00086074 MITCHAM -37.8219 145.1906 11.406147
## 15 ASN00086260 HEIDELBERG MMBW -37.7567 145.0533 11.579751
## 16 ASN00086378 BRUNSWICK -37.7667 144.9797 13.059611
## 17 ASN00086111 SPRINGVALE NECROPOLIS -37.9445 145.1764 13.245203
## 18 ASN00086369 SPRINGVALE (SANDOWN) -37.9535 145.1655 13.352636
## 19 ASN00086068 VIEWBANK (ARPANSA) -37.7408 145.0972 13.468157
## 20 ASN00086077 MOORABBIN AIRPORT -37.9800 145.0964 13.542852
## 21 ASN00086146 BEAUMARIS -37.9771 145.0273 13.548961
## 22 ASN00086362 DONCASTER (MANNINGHAM DEPOT) -37.7494 145.1703 15.129262
## 23 ASN00086351 BUNDOORA (LATROBE UNIVERSITY) -37.7163 145.0453 16.125457
## 24 ASN00086039 FLEMINGTON RACECOURSE -37.7915 144.9067 16.239778
## 25 ASN00086104 SCORESBY RESEARCH INSTITUTE -37.8710 145.2561 16.382188
## 26 ASN00086096 PRESTON RESERVOIR -37.7214 145.0059 16.408663
## 27 ASN00086230 BAYSWATER -37.8372 145.2558 16.509685
## 28 ASN00086379 RINGWOOD NORTH -37.7917 145.2433 17.010511
## 29 ASN00086101 RINGWOOD -37.8000 145.2500 17.158761
## 30 ASN00086313 WARRANDYTE -37.7469 145.2098 17.578887
## 31 ASN00086347 YARRA RIVER @ WARRANDYTE -37.7417 145.2167 18.416453
## 32 ASN00086224 DANDENONG -37.9785 145.2235 18.839479
## 33 ASN00086035 ELTHAM -37.7011 145.1547 19.172878
## 34 ASN00087038 MARIBYRNONG EXPLOSIVES FACTORY -37.7750 144.8767 19.432886
## 35 ASN00086324 FERNTREE GULLY (PROBERT) -37.8797 145.2964 19.993316
## 36 ASN00086027 CROYDON (SAMUEL STREET) -37.7903 145.2812 20.103933
## 37 ASN00086234 CROYDON (COUNCIL DEPOT) -37.7869 145.2847 20.535018
## 38 ASN00086038 ESSENDON AIRPORT -37.7276 144.9066 20.564229
## 39 ASN00087131 ALTONA (CITY OFFICES) -37.8633 144.8261 21.414594
## 40 ASN00087148 SUNSHINE (CITY OF BRINBANK) -37.7928 144.8344 22.000521
## 41 ASN00086250 PLENTY -37.6600 145.1244 22.747356
## 42 ASN00086256 FERNY CREEK -37.8833 145.3333 23.256162
## 43 ASN00086210 BONBEACH (CARRUM) -38.0651 145.1294 23.393049
## 44 ASN00086372 FERNY CREEK (DUNNS HILL) -37.8775 145.3364 23.465245
## 45 ASN00086365 MOOROOLBARK -37.7792 145.3197 23.701976
## 46 ASN00086251 UPWEY SHIRE COUNCIL -37.9144 145.3317 23.749365
## 47 ASN00086243 MOUNT DANDENONG GTV9 -37.8306 145.3500 24.802430
## 48 ASN00086059 KANGAROO GROUND -37.6830 145.2518 25.351527
## 49 ASN00086254 CARRUM DOWNS SEWER WORKS -38.0783 145.1733 25.907856
## 50 ASN00086036 EPPING -37.6312 144.9846 26.526359
## 51 ASN00086066 LILYDALE -37.7488 145.3416 26.875070
## 52 ASN00086076 MONTROSE -37.8019 145.3675 26.914609
## 53 ASN00086085 NARRE WARREN NORTH (NARRE WARR -37.9897 145.3356 27.399212
## 54 ASN00087031 LAVERTON RAAF -37.8565 144.7566 27.516720
## 55 ASN00087027 KEILOR (ARUNDEL) -37.6942 144.8342 27.737658
## 56 ASN00087177 LAVERTON COMPARISON -37.8633 144.7456 28.480727
## 57 ASN00086305 GREENVALE RESERVOIR -37.6369 144.9072 28.640881
## 58 ASN00086384 MELBOURNE AIRPORT COMPARISON -37.6750 144.8419 28.725743
## 59 ASN00087015 KEILOR -37.7025 144.8072 28.984935
##
## $bovenkarspel
## id name latitude longitude distance
## 1 NLE00101917 ENKHUIZEN 52.6917 5.2944 3.780363
## 2 NLE00109144 HOOGKARSPEL 52.6867 5.1669 5.143626
## 3 NLE00101928 MEDEMBLIK 52.7781 5.1014 12.746887
## 4 NLE00100501 HOORN 52.6444 5.0681 13.136277
## 5 NLE00102479 BERKHOUT 52.6428 4.9789 18.718869
## 6 NLE00109146 HOOGWOUD 52.7281 4.9608 19.065006
## 7 NLE00109174 KREILEROORD 52.8619 5.0953 20.464698
## 8 NLE00102134 STAVOREN 52.8967 5.3831 23.894441
## 9 NLE00109232 OBDAM 52.6775 4.8769 24.600539
## 10 NLE00109054 EDAM 52.5114 5.0467 24.701897
## 11 NLE00109250 OUDEMIRDUM 52.8608 5.5078 25.379621
## 12 NLE00109162 KOLHORN 52.7914 4.8919 25.540549
## 13 NLE00109354 WEST BEEMSTER 52.5817 4.9028 26.281190
## 14 NLE00101948 TOLLEBEEK 52.6719 5.6300 26.472774
## 15 NLE00101930 DEN OEVER 52.9217 5.0383 28.133541
## 16 NLE00101932 MARKEN 52.4600 5.1078 28.142012
## 17 NLE00109028 DE HAUKES 52.8783 4.9408 28.246661
## 18 NLE00109254 PURMEREND 52.5125 4.9506 28.575998
##
## $london
## id name latitude longitude distance
## 1 UKM00003772 HEATHROW 51.478 -0.461 25.42177
##
## $sydney
## id name latitude longitude distance
## 1 ASN00067019 PROSPECT RESERVOIR -33.8193 150.9127 3.769152
## 2 ASN00067017 GREYSTANES (BATHURST STREET) -33.8136 150.9392 4.135739
## 3 ASN00067070 MERRYLANDS (WELSFORD STREET) -33.8269 150.9767 5.020100
## 4 ASN00067114 ABBOTSBURY (FAIRFIELD CITY FAR -33.8667 150.8611 6.627566
## 5 ASN00067119 HORSLEY PARK EQUESTRIAN CENTRE -33.8511 150.8567 6.770114
## 6 ASN00067110 SEVEN HILLS (RADIO FM 103.2) -33.7858 150.9236 7.163157
## 7 ASN00067026 SEVEN HILLS (COLLINS ST) -33.7704 150.9318 8.852678
## 8 ASN00067020 LIVERPOOL (MICHAEL WENDEN CENT -33.9214 150.8861 8.913714
## 9 ASN00066137 BANKSTOWN AIRPORT AWS -33.9181 150.9864 9.189477
## 10 ASN00066134 GRANVILLE SHELL REFINERY -33.8322 151.0340 9.806921
## 11 ASN00066168 MILPERRA BRIDGE (GEORGES RIVER -33.9289 150.9831 10.049571
## 12 ASN00067042 KINGS LANGLEY (SOLANDER RD) -33.7610 150.9498 10.064021
## 13 ASN00067111 NORTH PARRAMATTA (BURNSIDE HOM -33.7931 151.0167 10.206744
## 14 ASN00067109 BAULKHAM HILLS EUCALYPTUS CT -33.7678 150.9814 10.300292
## 15 ASN00066124 PARRAMATTA NORTH (MASONS DRIVE -33.7917 151.0181 10.404864
## 16 ASN00066050 POTTS HILL RESERVOIR -33.8933 151.0346 10.790772
## 17 ASN00066164 ROOKWOOD (HAWTHORNE AVE) -33.8771 151.0577 12.169844
## 18 ASN00067112 NORTH ROCKS (MUIRFIELD GOLF CL -33.7672 151.0186 12.319787
## 19 ASN00066195 SYDNEY OLYMPIC PARK (SYDNEY OL -33.8521 151.0646 12.431978
## 20 ASN00066070 STRATHFIELD GOLF CLUB -33.8805 151.0631 12.748603
## 21 ASN00066054 REVESBY (PATEN STREET) -33.9474 151.0065 12.928587
## 22 ASN00067076 QUAKERS HILL TREATMENT WORKS -33.7366 150.8758 13.567795
## 23 ASN00066185 CARLINGFORD (BARELLAN AV) -33.7801 151.0587 14.205035
## 24 ASN00066191 GLENFIELD (HARROW ROAD) -33.9770 150.9042 14.321038
## 25 ASN00067117 HOLSWORTHY CONTROL RANGE -33.9795 150.9254 14.405998
## 26 ASN00067102 ST CLAIR (JUBA CLOSE) -33.8044 150.7778 14.945410
## 27 ASN00067100 CASTLE HILL (KATHLEEN AVE) -33.7260 150.9944 15.017779
## 28 ASN00067089 WEST PENNANT HILLS (CUMBERLAND -33.7459 151.0402 15.416884
## 29 ASN00067003 COLYTON (CARPENTER ST) -33.7770 150.7877 15.450666
## 30 ASN00067098 WEST PENNANT HILLS (ORATAVA A -33.7487 151.0449 15.478987
## 31 ASN00066013 CONCORD GOLF CLUB -33.8523 151.0985 15.562401
## 32 ASN00067061 ROSSMORE (SOUTH CREEK) -33.9353 150.7819 16.638119
## 33 ASN00066048 CONCORD (BRAYS RD) -33.8483 151.1105 16.669913
## 34 ASN00067037 SCHOFIELDS BOUNDARY RD -33.6947 150.8868 17.724215
## 35 ASN00066194 CANTERBURY RACECOURSE AWS -33.9057 151.1134 18.028240
## 36 ASN00066148 PEAKHURST GOLF CLUB -33.9700 151.0638 18.179759
## 37 ASN00066034 ABBOTSFORD (BLACKWALL POINT RD -33.8507 151.1295 18.423361
## 38 ASN00067116 WILLMOT (RESOLUTION AVE) -33.7231 150.7997 18.550317
## 39 ASN00066156 MACQUARIE PARK (WILLANDRA VILL -33.7791 151.1121 18.579019
## 40 ASN00066047 PENNANT HILLS (YARRARA ROAD) -33.7324 151.0767 18.835558
## 41 ASN00066190 INGLEBURN (SACKVILLE STREET) -34.0117 150.8647 18.962689
## 42 ASN00067108 BADGERYS CREEK AWS -33.8969 150.7281 19.355573
## 43 ASN00066181 OATLEY (WORONORA PARADE) -33.9766 151.0766 19.523783
## 44 ASN00066004 BEXLEY BOWLING CLUB -33.9430 151.1098 19.553323
## 45 ASN00067086 DURAL (OLD NORTHERN ROAD) -33.6867 151.0250 20.170027
## 46 ASN00066036 MARRICKVILLE GOLF CLUB -33.9186 151.1402 20.849104
## 47 ASN00066131 RIVERVIEW OBSERVATORY -33.8258 151.1556 21.009524
## 48 ASN00067104 BOX HILL (HYNDS ROAD) -33.6617 150.9000 21.120894
## 49 ASN00066189 WEST PYMBLE (WYUNA ROAD) -33.7693 151.1380 21.209116
## 50 ASN00067084 ORCHARD HILLS TREATMENT WORKS -33.8020 150.7069 21.288391
## 51 ASN00066204 OYSTER BAY (GREEN POINT ROAD) -34.0009 151.0738 21.391107
## 52 ASN00066158 TURRAMURRA (KISSING POINT ROAD -33.7366 151.1271 22.152621
## 53 ASN00066120 GORDON GOLF CLUB -33.7617 151.1462 22.258367
## 54 ASN00066078 LUCAS HEIGHTS (ANSTO) -34.0517 150.9800 22.897282
## 55 ASN00067015 BRINGELLY (MARYLAND) -33.9696 150.7250 23.124628
## 56 ASN00068160 CAMPBELLTOWN (KENTLYN (GEORGES -34.0542 150.8772 23.222412
## 57 ASN00068250 CAMDEN VALLEY GOLF RESORT -34.0128 150.7675 23.504569
## 58 ASN00066157 PYMBLE (CANISIUS COLLEGE) -33.7371 151.1521 24.058869
## 59 ASN00066058 SANS SOUCI (PUBLIC SCHOOL) -33.9942 151.1292 24.391064
## 60 ASN00067022 GALSTON (ROWLAND VILLAGE) -33.6550 151.0553 24.583503
## 61 ASN00068231 RUSE (DENISON STREET) -34.0630 150.8489 24.837610
## 62 ASN00066114 NORTH TURRAMURRA (DRYDEN RD) -33.7179 151.1470 24.858762
## 63 ASN00066037 SYDNEY AIRPORT AMO -33.9465 151.1731 24.870760
## 64 ASN00066062 SYDNEY (OBSERVATORY HILL) -33.8607 151.2050 25.421751
## 65 ASN00066011 CHATSWOOD BOWLING CLUB -33.8000 151.2000 25.553205
## 66 ASN00067115 GLENMORE PARK (CARTWRIGHT CL) -33.7826 150.6619 25.877100
## 67 ASN00066006 SYDNEY BOTANIC GARDENS -33.8662 151.2160 26.470162
## 68 ASN00066080 CASTLE COVE (ROSEBRIDGE AVE) -33.7809 151.2044 26.489163
## 69 ASN00066176 AUDLEY (ROYAL NATIONAL PARK) -34.0658 151.0567 26.689966
## 70 ASN00067029 WALLACIA POST OFFICE -33.8637 150.6410 26.729649
## 71 ASN00066206 ST IVES (RICHMOND AVENUE) -33.7096 151.1730 27.351861
## 72 ASN00067113 PENRITH LAKES AWS -33.7195 150.6783 27.416523
## 73 ASN00068257 CAMPBELLTOWN (MOUNT ANNAN) -34.0615 150.7735 27.594122
## 74 ASN00066073 RANDWICK RACECOURSE -33.9105 151.2276 28.284461
## 75 ASN00068254 MOUNT ANNAN BOTANIC GARDEN -34.0673 150.7678 28.418732
## 76 ASN00066160 CENTENNIAL PARK -33.8959 151.2341 28.535385
## 77 ASN00067031 WINDSOR BOWLING CLUB -33.6100 150.8151 28.724326
## 78 ASN00066188 BELROSE (EVELYN PLACE) -33.7402 151.2173 29.221247
## 79 ASN00066052 RANDWICK BOWLING CLUB -33.9096 151.2419 29.545881
## 80 ASN00066086 CRONULLA STP -34.0313 151.1642 29.549535
## 81 ASN00067010 GLENORIE (OLD NORTHERN RD) -33.5908 151.0094 29.742533
##
## $genesee1
## id name latitude longitude distance
## 1 USC00201150 MI BURTON 4N 43.0675 -83.5919 3.979309
## 2 US1MIGN0010 MI BURTON 0.9 NNW 43.0085 -83.6274 9.064849
## 3 US1MIGN0008 MI MOUNT MORRIS 3.1 WSW 43.1057 -83.7580 10.538333
## 4 US1MIGN0014 MI DAVISON 3.3 SW 43.0003 -83.5684 11.159857
## 5 US1MIGN0005 MI DAVISON 0.7 SSW 43.0219 -83.5246 11.431375
## 6 USC00202851 MI FLINT 7 W 43.0378 -83.7694 12.725462
## 7 USC00201645 MI CLIO 43.1794 -83.7369 13.193328
## 8 US1MIGN0009 MI BURTON 3.3 SW 42.9613 -83.6636 14.569099
## 9 USW00014826 MI FLINT BISHOP INTL AP 42.9667 -83.7494 16.797891
## 10 US1MIGN0023 MI GRAND BLANC 3.8 WNW 42.9440 -83.6886 16.919078
## 11 US1MISG0004 MI BIRCH RUN 2.6 ESE 43.2291 -83.7470 18.146491
## 12 US1MIGN0020 MI SWARTZ CREEK 2.0 NNE 42.9897 -83.8166 18.824526
## 13 US1MIGN0015 MI FLINT 6.4 SSW 42.9326 -83.7210 19.001794
## 14 US1MIGN0018 MI GRAND BLANC 0.7 SE 42.9187 -83.6079 19.132279
## 15 USC00203278 MI GOODRICH 42.9164 -83.5097 21.640755
## 16 USC00204659 MI LAPEER 2W 43.0581 -83.3606 22.167570
## 17 US1MIGN0022 MI GRAND BLANC 2.9 SE 42.8909 -83.5858 22.428899
## 18 US1MIGN0004 MI MONTROSE 0.4 NW 43.1794 -83.8987 23.962697
## 19 USC00205488 MI MILLINGTON 3 SE 43.2836 -83.4792 24.756898
## 20 US1MILP0003 MI LAPEER 1.1 SSW 43.0316 -83.3293 25.277892
## 21 USC00204655 MI LAPEER WWTP 43.0608 -83.3075 26.394851
## 22 USC00202955 MI FRANKENMUTH 1SE 43.3194 -83.7161 26.445482
##
## $genesee2
## id name latitude longitude distance
## 1 USC00201150 MI BURTON 4N 43.0675 -83.5919 3.979309
## 2 US1MIGN0010 MI BURTON 0.9 NNW 43.0085 -83.6274 9.064849
## 3 US1MIGN0008 MI MOUNT MORRIS 3.1 WSW 43.1057 -83.7580 10.538333
## 4 US1MIGN0014 MI DAVISON 3.3 SW 43.0003 -83.5684 11.159857
## 5 US1MIGN0005 MI DAVISON 0.7 SSW 43.0219 -83.5246 11.431375
## 6 USC00202851 MI FLINT 7 W 43.0378 -83.7694 12.725462
## 7 US1MIGN0024 MI CLIO 0.4 SW 43.1725 -83.7423 12.930649
## 8 USC00201645 MI CLIO 43.1794 -83.7369 13.193328
## 9 US1MIGN0009 MI BURTON 3.3 SW 42.9613 -83.6636 14.569099
## 10 USW00014826 MI FLINT BISHOP INTL AP 42.9667 -83.7494 16.797891
## 11 US1MIGN0023 MI GRAND BLANC 3.8 WNW 42.9440 -83.6886 16.919078
## 12 US1MISG0004 MI BIRCH RUN 2.6 ESE 43.2291 -83.7470 18.146491
## 13 US1MIGN0020 MI SWARTZ CREEK 2.0 NNE 42.9897 -83.8166 18.824526
## 14 US1MIGN0015 MI FLINT 6.4 SSW 42.9326 -83.7210 19.001794
## 15 US1MIGN0018 MI GRAND BLANC 0.7 SE 42.9187 -83.6079 19.132279
## 16 USC00203278 MI GOODRICH 42.9164 -83.5097 21.640755
## 17 USC00204659 MI LAPEER 2W 43.0581 -83.3606 22.167570
## 18 US1MIGN0022 MI GRAND BLANC 2.9 SE 42.8909 -83.5858 22.428899
## 19 US1MIGN0004 MI MONTROSE 0.4 NW 43.1794 -83.8987 23.962697
## 20 USC00205488 MI MILLINGTON 3 SE 43.2836 -83.4792 24.756898
## 21 US1MILP0003 MI LAPEER 1.1 SSW 43.0316 -83.3293 25.277892
## 22 USC00204655 MI LAPEER WWTP 43.0608 -83.3075 26.394851
## 23 USC00202955 MI FRANKENMUTH 1SE 43.3194 -83.7161 26.445482
##
## $columbus
## id name latitude longitude
## 1 US1OHFR0018 OH COLUMBUS 2.4 WNW 39.9977 -83.0323
## 2 US1OHFR0025 OH COLUMBUS 2.8 WSW 39.9804 -83.0397
## 3 US1OHFR0003 OH GRANDVIEW HEIGHTS 0.1 N 39.9810 -83.0401
## 4 USC00331785 OH COLUMBUS WCMH 40.0250 -83.0269
## 5 US1OHFR0034 OH COLUMBUS 3.6 NW 40.0191 -83.0437
## 6 US1OHFR0020 OH COLUMBUS 3.5 NE 40.0287 -82.9477
## 7 US1OHFR0001 OH UPPER ARLINGTON 0.9 E 40.0279 -83.0543
## 8 US1OHFR0021 OH MARBLE CLIFF 1.1 WNW 39.9931 -83.0786
## 9 US1OHFR0007 OH UPPER ARLINGTON 1.3 SSW 40.0112 -83.0832
## 10 USW00014821 OH COLUMBUS PORT COLUMBUS INTL AP 39.9914 -82.8808
## 11 USC00331783 OH COLUMBUS-VALLEY CROSSING 39.9047 -82.9200
## 12 US1OHFR0012 OH UPPER ARLINGTON 2.4 NNW 40.0604 -83.0815
## 13 USC00331777 OH COLUMBUS-HAP CREMEAN WP 40.0603 -82.8942
## 14 US1OHFR0024 OH COLUMBUS 9.3 NNE 40.0925 -82.9582
## 15 USW00004804 OH COLUMBUS OHIO STATE UNIV AP 40.0781 -83.0781
## 16 US1OHFR0037 OH REYNOLDSBURG 1.6 W 39.9588 -82.8294
## 17 US1OHFR0016 OH DUBLIN 3.7 ESE 40.0923 -83.0725
## 18 US1OHFR0022 OH GALLOWAY 3.1 N 39.9561 -83.1592
## 19 USC00331779 OH COLUMBUS-PARSONS AVE. 39.8469 -82.9872
## 20 USC00338951 OH WESTERVILLE 40.1264 -82.9433
## 21 US1OHFR0010 OH WESTERVILLE 0.2 WNW 40.1226 -82.9213
## 22 US1OHFR0030 OH HILLIARD 1.8 W 40.0344 -83.1768
## 23 US1OHFR0008 OH NEW ALBANY 2.8 SSE 40.0403 -82.7980
## 24 US1OHFR0002 OH DUBLIN 3.2 ENE 40.1299 -83.0742
## 25 US1OHLC0002 OH PATASKALA 4.4 WNW 40.0273 -82.7490
## 26 US1OHFF0005 OH PICKERINGTON 2.7 NNE 39.9263 -82.7469
## 27 US1OHDL0002 OH WESTERVILLE 4.0 N 40.1790 -82.9256
## 28 US1OHFR0023 OH HARRISBURG 3.7 WNW 39.8378 -83.2321
## 29 US1OHLC0011 OH PATASKALA 2.0 NE 40.0240 -82.6511
## distance
## 1 4.106137
## 2 4.234920
## 3 4.270197
## 4 5.909011
## 5 6.310790
## 6 6.504242
## 7 7.639623
## 8 7.687720
## 9 8.664212
## 10 9.389591
## 11 10.282003
## 12 11.858973
## 13 12.094496
## 14 12.799033
## 15 13.238469
## 16 13.887609
## 17 14.326951
## 18 14.662096
## 19 14.801971
## 20 16.757176
## 21 16.900247
## 22 17.021110
## 23 17.673463
## 24 18.143413
## 25 21.190424
## 26 21.564691
## 27 22.796070
## 28 26.008132
## 29 29.278406
##
## $bronx
## id name latitude longitude distance
## 1 USW00014732 NY NEW YORK LAGUARDIA AP 40.7794 -73.8803 5.616756
## 2 USW00094728 NY NEW YORK CNTRL PK TWR 40.7789 -73.9692 6.167420
## 3 USC00300961 NY BRONX 40.8369 -73.8494 6.230297
## 4 US1NJBG0018 NJ PALISADES PARK 0.2 WNW 40.8481 -74.0002 7.435652
## 5 US1NJBG0003 NJ TENAFLY 1.3 W 40.9147 -73.9775 11.587163
## 6 US1NYQN0002 NY MIDDLE VILLAGE 0.5 SW 40.7145 -73.8819 12.161951
## 7 USW00094741 NJ TETERBORO AP 40.8500 -74.0614 12.354793
## 8 US1NJBG0001 NJ BERGENFIELD 0.3 SW 40.9213 -74.0020 13.206762
## 9 US1NJBG0012 NJ WOOD RIDGE 0.6 SE 40.8420 -74.0830 13.930427
## 10 US1NJBG0033 NJ WOOD RIDGE 0.6 NNW 40.8536 -74.0943 15.131881
## 11 US1NYWC0009 NY NEW ROCHELLE 1.3 S 40.9040 -73.7770 15.226895
## 12 US1NJBG0013 NJ RUTHERFORD 1.2 N 40.8373 -74.1065 15.809146
## 13 US1NYKN0025 NY BROOKLYN 3.1 NW 40.6846 -73.9867 16.069963
## 14 US1NJBG0031 NJ DEMAREST 0.6 NNW 40.9628 -73.9600 16.230719
## 15 US1NJBG0002 NJ SADDLE BROOK TWP 0.6 E 40.9027 -74.0834 16.534408
## 16 US1NJBG0011 NJ NORTH ARLINGTON 0.7 NE 40.7944 -74.1190 16.988985
## 17 US1NJBG0008 NJ SADDLE BROOK TWP 0.3 NNE 40.9071 -74.0934 17.505118
## 18 USC00286146 NJ NEW MILFORD 40.9611 -74.0158 17.635536
## 19 US1NJBG0015 NJ NORTH ARLINGTON 0.7 WNW 40.7915 -74.1398 18.769309
## 20 US1NJHD0002 NJ KEARNY 1.7 NW 40.7729 -74.1409 19.318492
## 21 US1NJBG0005 NJ WESTWOOD 0.8 ESE 40.9830 -74.0159 19.836072
## 22 US1NJBG0010 NJ RIVER VALE TWP 1.5 S 40.9915 -74.0123 20.587159
## 23 US1NYNS0007 NY FLORAL PARK 0.4 W 40.7230 -73.7110 20.642010
## 24 US1NJHD0001 NJ HARRISON 0.3 N 40.7480 -74.1518 21.094543
## 25 USC00283704 NJ HARRISON 40.7514 -74.1567 21.338273
## 26 US1NJBG0020 NJ PARAMUS 1.8 NNW 40.9682 -74.0902 21.822558
## 27 USC00302129 NY DOBBS FERRY-ARDSLEY 41.0072 -73.8344 22.023427
## 28 US1NJBG0017 NJ GLEN ROCK 0.7 SSE 40.9511 -74.1183 22.145027
## 29 US1NJES0020 NJ BLOOMFIELD 1.7 S 40.7850 -74.1885 22.932509
## 30 US1NYKN0003 NY BROOKLYN 2.4 SW 40.6194 -73.9859 22.986706
## 31 US1NYWC0005 NY HARRISON 4.1 SSW 40.9639 -73.7232 23.014851
## 32 USC00307587 NY SEA CLIFF 40.8506 -73.6483 23.109762
## 33 US1NJBG0037 NJ GLEN ROCK 0.4 WNW 40.9614 -74.1328 23.815579
## 34 US1NJPS0014 NJ HAWTHORNE 1.0 SSE 40.9436 -74.1523 23.880745
## 35 USC00289832 NJ WOODCLIFF LAKE 41.0139 -74.0425 23.891667
## 36 US1NJES0015 NJ MONTCLAIR 2.2 NNE 40.8565 -74.2004 23.935385
## 37 USW00094789 NY NEW YORK JFK INTL AP 40.6386 -73.7622 24.159135
## 38 US1NJPS0017 NJ WOODLAND PARK 0.1 NW 40.8918 -74.1960 24.547061
## 39 US1NJPS0005 NJ HAWTHORNE 0.4 S 40.9519 -74.1577 24.787058
## 40 US1NJES0011 NJ CEDAR GROVE TWP 0.9 NE 40.8648 -74.2157 25.368252
## 41 USC00305796 NY NY AVE V BROOKLYN 40.5939 -73.9808 25.658206
## 42 US1NJPS0018 NJ PATERSON 2.0 W 40.9163 -74.2005 25.903423
## 43 USW00014734 NJ NEWARK INTL AP 40.6825 -74.1694 25.982975
## 44 US1NJPS0003 NJ LITTLE FALLS TWP 0.2 NNW 40.8788 -74.2205 26.107408
## 45 US1NJPS0012 NJ LITTLE FALLS TWP 0.5 WNW 40.8796 -74.2270 26.658883
## 46 USC00284887 NJ LITTLE FALLS 40.8858 -74.2261 26.764590
## 47 US1NJES0024 NJ CEDAR GROVE TWP 0.4 W 40.8557 -74.2356 26.845270
## 48 US1NYNS0014 NY LYNBROOK 0.3 NW 40.6623 -73.6780 26.891776
## 49 USC00285503 NJ MIDLAND PARK 40.9939 -74.1453 27.062890
## 50 USC00305377 NY MINEOLA 40.7328 -73.6183 27.191818
## 51 US1NJPS0004 NJ NORTH HALEDON 0.6 N 40.9713 -74.1856 27.953822
## 52 US1NJES0010 NJ VERONA TWP 0.7 SW 40.8255 -74.2531 28.035405
## 53 US1NJES0021 NJ VERONA TWP 0.6 WSW 40.8305 -74.2539 28.119240
## 54 US1NJES0004 NJ NORTH CALDWELL 0.6 SSE 40.8576 -74.2523 28.265572
## 55 US1NJPS0008 NJ WAYNE TWP 1.1 ESE 40.9412 -74.2267 29.094312
## 56 US1NYWC0003 NY WHITE PLAINS 3.1 NNW 41.0639 -73.7722 29.826697
## 57 US1NYNS0009 NY MILL NECK 1.1 SW 40.8704 -73.5717 29.828998
## 58 US1NYRL0005 NY WEST NYACK 1.3 WSW 41.0835 -73.9930 29.934369Not all the locations have stations nearby. Therefore, I will omit them from the weather data evaluation using the following code.
has_stations <- sapply(stations, function(x) nrow(x) > 0)
outbreak_loc_true <- outbreak_loc %>% filter(has_stations)
outbreak_loc_true## id file_id latitude longitude year_min date_min
## 1 pittsburgh pittsburgh 40.43 -79.98 2002 2002-01-01
## 2 quebec quebec 46.85 -71.34 2002 2002-01-01
## 3 miyazaki miyazaki 31.89 131.34 1992 1992-01-01
## 4 pamplona pamplona 42.81 -1.65 1996 1996-01-01
## 5 rapid city rapid_city 44.06 -103.22 1995 1995-01-01
## 6 sarpsborg sarpsborg 59.28 11.08 1995 1995-01-01
## 7 murcia murcia 37.98 -1.12 1991 1991-01-01
## 8 melbourne melbourne -37.86 145.07 1990 1990-01-01
## 9 bovenkarspel bovenkarspel 52.70 5.24 1989 1989-01-01
## 10 london london 51.52 -0.10 1979 1979-01-01
## 11 sydney sydney -33.85 150.93 2006 2006-01-01
## 12 genesee1 genesee1 43.09 -83.63 2004 2004-01-01
## 13 genesee2 genesee2 43.09 -83.63 2005 2005-01-01
## 14 columbus columbus 39.98 -82.99 2003 2003-01-01
## 15 bronx bronx 40.82 -73.92 2005 2005-01-01
## year_max date_max onset before_onset
## 1 2012 2012-12-31 2012-08-26 2012-08-12
## 2 2012 2012-12-31 2012-07-18 2012-07-04
## 3 2002 2002-12-31 2002-07-18 2002-07-04
## 4 2006 2006-12-31 2006-06-01 2006-05-18
## 5 2005 2005-12-31 2005-05-26 2005-05-12
## 6 2005 2005-12-31 2005-05-12 2005-04-28
## 7 2001 2001-12-31 2001-06-26 2001-06-12
## 8 2000 2000-12-31 2000-04-17 2000-04-03
## 9 1999 1999-12-31 1999-02-25 1999-02-11
## 10 1989 1989-12-31 1989-01-01 1988-12-18
## 11 2016 2016-12-31 2016-04-25 2016-04-11
## 12 2014 2014-12-31 2014-06-06 2014-05-23
## 13 2015 2015-12-31 2015-05-04 2015-04-20
## 14 2013 2013-12-31 2013-07-09 2013-06-25
## 15 2015 2015-12-31 2015-07-12 2015-06-28Using the countyweather codes I can gather the data for each station in a loop. The code gathers the weather data for each stations and averages them. Then I saved all the data as rds. files because they take a long time to gather. The data is saved in a folder I created called “weather_files/”
for(i in which(has_stations))
{
meteo_df <- meteo_pull_monitors(monitors = stations[[i]]$id,
keep_flags = FALSE,
date_min = outbreak_loc$date_min[i],
date_max = outbreak_loc$date_max[i],
var = c("prcp","snow","snwd","tmax","tmin","tavg"))
coverage_df <- rnoaa::meteo_coverage(meteo_df, verbose = FALSE)
filtered <- countyweather:::filter_coverage(coverage_df, 0.90)
good_monitors <- unique(filtered$id)
filtered_data <- dplyr::filter(meteo_df, id %in% good_monitors)
averaged <- countyweather:::ave_weather(filtered_data)
# For metrics that are reported in tenths of units (precipitation
# and temperature), divide by 10 to get values in degrees Celsius and
# millimeters
which_tenth_units <- which(colnames(averaged) %in%
c("prcp", "tavg", "tmax", "tmin"))
averaged[ , which_tenth_units] <- averaged[ , which_tenth_units] / 10
file_name <- paste0("weather_files/", outbreak_loc$file_id[i], ".rds")
saveRDS(averaged, file_name)
#readRDS(file_name)
}Now that all of the data is gathered and averaged I can plot the data. The loop will go through the files in order which is in alphabetical order. Therefore I must order my outbreak data frame into alphabetical order too. I will rename this data frame as df_stations for plotting.
## id file_id latitude longitude year_min date_min
## 1 bovenkarspel bovenkarspel 52.70 5.24 1989 1989-01-01
## 2 bronx bronx 40.82 -73.92 2005 2005-01-01
## 3 columbus columbus 39.98 -82.99 2003 2003-01-01
## 4 genesee1 genesee1 43.09 -83.63 2004 2004-01-01
## 5 genesee2 genesee2 43.09 -83.63 2005 2005-01-01
## 6 london london 51.52 -0.10 1979 1979-01-01
## 7 melbourne melbourne -37.86 145.07 1990 1990-01-01
## 8 miyazaki miyazaki 31.89 131.34 1992 1992-01-01
## 9 murcia murcia 37.98 -1.12 1991 1991-01-01
## 10 pamplona pamplona 42.81 -1.65 1996 1996-01-01
## 11 pittsburgh pittsburgh 40.43 -79.98 2002 2002-01-01
## 12 quebec quebec 46.85 -71.34 2002 2002-01-01
## 13 rapid city rapid_city 44.06 -103.22 1995 1995-01-01
## 14 sarpsborg sarpsborg 59.28 11.08 1995 1995-01-01
## 15 sydney sydney -33.85 150.93 2006 2006-01-01
## year_max date_max onset before_onset
## 1 1999 1999-12-31 1999-02-25 1999-02-11
## 2 2015 2015-12-31 2015-07-12 2015-06-28
## 3 2013 2013-12-31 2013-07-09 2013-06-25
## 4 2014 2014-12-31 2014-06-06 2014-05-23
## 5 2015 2015-12-31 2015-05-04 2015-04-20
## 6 1989 1989-12-31 1989-01-01 1988-12-18
## 7 2000 2000-12-31 2000-04-17 2000-04-03
## 8 2002 2002-12-31 2002-07-18 2002-07-04
## 9 2001 2001-12-31 2001-06-26 2001-06-12
## 10 2006 2006-12-31 2006-06-01 2006-05-18
## 11 2012 2012-12-31 2012-08-26 2012-08-12
## 12 2012 2012-12-31 2012-07-18 2012-07-04
## 13 2005 2005-12-31 2005-05-26 2005-05-12
## 14 2005 2005-12-31 2005-05-12 2005-04-28
## 15 2016 2016-12-31 2016-04-25 2016-04-11PLOT 1
Outbreak Distribution
This plot is divided by outbreaks in the northern and southern hemisphere. This allows us to see when the outbreaks generally occur in the year.
PLOT 2
10 years for all data
These plots allow for a quick glance into all the weather variables for each location.
## Warning: Removed 4 rows containing missing values (geom_path).
## Warning: Removed 19 rows containing missing values (geom_path).
## Warning: Removed 27 rows containing missing values (geom_path).
PLOT 3
TMAX and TMIN
## Warning: Removed 1098 rows containing missing values (geom_path).
## Warning: Removed 7 rows containing missing values (geom_path).
## Warning: Removed 3 rows containing missing values (geom_path).
## Warning: Removed 55 rows containing missing values (geom_path).
PLOT 4
Precipitation
I also made a loop to plot graphs and histograms of the data with lines indicating each day before the start of the outbreak for a total of 14 days.A plot of the percentiles is also included.
## Warning: Removed 946 rows containing non-finite values (stat_bin).## Warning: Removed 4 rows containing missing values (geom_vline).
## Warning: Removed 24 rows containing missing values (geom_path).
## Warning: Removed 2690 rows containing non-finite values (stat_bin).## Warning: Removed 1 rows containing missing values (geom_vline).
## Warning: Removed 27 rows containing missing values (geom_path).
## Warning: Removed 27 rows containing non-finite values (stat_bin).
PLOT 5
TMAX
## Warning: Removed 549 rows containing missing values (geom_path).
## Warning: Removed 549 rows containing non-finite values (stat_bin).
## Warning: Removed 3 rows containing missing values (geom_path).
## Warning: Removed 1038 rows containing non-finite values (stat_bin).## Warning: Removed 8 rows containing missing values (geom_vline).
## Warning: Removed 8 rows containing missing values (position_stack).
## Warning: Removed 107 rows containing non-finite values (stat_bin).
## Warning: Removed 975 rows containing non-finite values (stat_bin).
## Warning: Removed 28 rows containing missing values (geom_path).
## Warning: Removed 28 rows containing non-finite values (stat_bin).
PLOT 6
TMIN
## Warning: Removed 549 rows containing missing values (geom_path).
## Warning: Removed 549 rows containing non-finite values (stat_bin).
## Warning: Removed 4 rows containing missing values (geom_path).
## Warning: Removed 1586 rows containing non-finite values (stat_bin).## Warning: Removed 9 rows containing missing values (geom_vline).
## Warning: Removed 9 rows containing missing values (position_stack).
## Warning: Removed 3 rows containing missing values (geom_path).
## Warning: Removed 1594 rows containing non-finite values (stat_bin).## Warning: Removed 5 rows containing missing values (geom_vline).
## Warning: Removed 5 rows containing missing values (position_stack).
## Warning: Removed 975 rows containing non-finite values (stat_bin).
## Warning: Removed 27 rows containing missing values (geom_path).
## Warning: Removed 27 rows containing non-finite values (stat_bin).
